Instructions to use selimyagci/pm_dom_llama_quantized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Adapters
How to use selimyagci/pm_dom_llama_quantized with Adapters:
from adapters import AutoAdapterModel model = AutoAdapterModel.from_pretrained("meta-llama/Llama-3.2-1B") model.load_adapter("selimyagci/pm_dom_llama_quantized", set_active=True) - Notebooks
- Google Colab
- Kaggle
Adapter selimyagci/pm_dom_llama_quantized for meta-llama/Llama-3.2-1B
An adapter for the meta-llama/Llama-3.2-1B model that was trained on the None dataset.
This adapter was created for usage with the Adapters library.
Usage
First, install adapters:
pip install -U adapters
Now, the adapter can be loaded and activated like this:
from adapters import AutoAdapterModel
model = AutoAdapterModel.from_pretrained("meta-llama/Llama-3.2-1B")
adapter_name = model.load_adapter("selimyagci/pm_dom_llama_quantized", set_active=True)
Architecture & Training
Evaluation results
Citation
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